Establishing the sleep disruption characteristics of wind turbine compared to traffic noise using quantitative electroencephalography with spectral power analysis

Author: Claire Dunbar

Dunbar, Claire, 2023 Establishing the sleep disruption characteristics of wind turbine compared to traffic noise using quantitative electroencephalography with spectral power analysis, Flinders University, College of Education, Psychology and Social Work

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Sleep is important for health and normal physiological and psychological wellbeing and

daytime function. A well-known source of sleep disruption is nocturnal exposure to noise such as

from air, road, and rail traffic. The consequences of consistently disrupted sleep can result in serious

health deficits including hypertension, cardiovascular disease, impaired mental health, and daytime

functioning. Therefore, all reports of significant sleep disruption warrant examination using

appropriate sleep and noise assessment methods. Another source of nocturnal noise, increasing in

its presence as the world attempts to reduce carbon emissions, is from wind farms. Noise from wind

farms has more dominant low frequency components compared to other noise sources and its

effects on sleep are currently unclear and need further investigation. Subjective reports of impaired

sleep in some individuals living in the vicinity of wind farms have prompted the need for

comprehensive investigation of the possible impact of wind farm noise (WFN) on sleep using

objective measures of sleep in well controlled experimental studies. The gold-standard objective

measure of sleep is polysomnography (PSG). However, the standard macrostructure sleep measures

such as total sleep time and time spent in different sleep stages may not be sufficiently sensitive to

capture more subtle changes within the EEG that could potentially differentially impact effective

sleep quality and measures of daytime functioning.

This thesis used quantitative electroencephalography (qEEG) to objectively assess and

compare the impact of traffic noise and wind farm noise on sleep. qEEG is likely to be more

sensitive than traditional sleep assessment methods for evaluating noise effects on the sleep EEG.

For example, traditional PSG analysis may find no effects of WFN on total sleep time, or the

amount of time spent in individual sleep stages. However, it must be recognised that the definition

of deeper sleep stages as distinguished from lighter stages of sleep is based on manual scoring of 30

second epochs and somewhat arbitrary and crude criteria dividing sleep stages. Potentially

important differences within any given sleep stage in terms of amplitude, frequency, and power

could easily be missed. These differences may importantly contribute to the functional effects of

deep sleep on the overall recuperative properties of the whole sleep period. If qEEG is sensitive to

noise exposure but macrostructural analysis is not, qEEG analysis may be recommended for more

comprehensive assessments of sleep beyond traditional macrostructure sleep analysis. Furthermore,

such results would provide valuable feedback for informing noise guidelines and mitigation

strategies which are currently based on more typically mid to high frequency dominated noise

sources such as road traffic noise.

Keywords: road traffic noise, wind turbine noise, sleep, sleep disruption, spectral power, quantitative electroencephalography, polysomnography

Subject: Psychology thesis

Thesis type: Doctor of Philosophy
Completed: 2023
School: College of Education, Psychology and Social Work
Supervisor: Leon Lack